CGR

Coarse-Grained Group Recommendation

The project aims at building algorithms and open frameworks for group recommendation in case of limited bandwith available.

Recommender systems have been developed to deal with information overload in computational societies. In order to support recommendations in social activities (e.g., people traveling together or going to a restaurant/museum together), algorithms able to provide group recommendations were developed.

A special type of group recommendation is needed when technological constraints limit the bandwidth available for the recommendation process. In such cases the first result that the algorithm has to compute is a proper identification of groups, in order to produce a recommendation that maximizes users satisfaction and respects the limits imposed by the system.

Coarse-Grain Group recommendation is a novel approach for group recommendation that automatically detects groups of users with similar preferences.